eotransform-xarray

Implements transformations on xarray data structures, usually representing raster data which can then be streamed using eotransform. Project badge

https://github.com/tuw-geo/eotransform-xarray

Science Score: 85.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • Institutional organization owner
    Organization tuw-geo has institutional domain (geo.tuwien.ac.at)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.0%) to scientific vocabulary
Last synced: 8 months ago · JSON representation ·

Repository

Implements transformations on xarray data structures, usually representing raster data which can then be streamed using eotransform. Project badge

Basic Info
  • Host: GitHub
  • Owner: TUW-GEO
  • Language: Python
  • Default Branch: main
  • Size: 248 KB
Statistics
  • Stars: 0
  • Watchers: 3
  • Forks: 0
  • Open Issues: 0
  • Releases: 23
Created over 3 years ago · Last pushed about 2 years ago
Metadata Files
Readme Citation

README.md

Test with coverage DOI

eotransform-xarray

What can I use eotransform-xarray for?

The eotransform-xarray package provides common transformations on raster data represented as xarray data structures, following the Transformer protocol of eotransform. This makes them easy to mix and match, and you can quickly chain processing pipelines, using other eotransform protocols. Additionally, processing pipelines constructed from these Transformers, can be automatically applied to the streamed_process function from eotransform, to benefit from I/O hiding.

Getting Started

Installation

bash pip install eotransform-xarray

Example: streamed processing pipeline

In the following example swath data is resampled, masked and written out as a GeoTIFF stack.

py resample = ResampleWithGauss(swath_geometry, raster_geometry, sigma=2e5, neighbours=4, lookup_radius=1e6) mask = MaskWhere(lambda x: x > 2, np.nan) squeeze = Squeeze() with ThreadPoolExecutor(max_workers=3) as ex: pipeline = Compose([resample, mask, squeeze]) streamed_process(input_src, pipeline, SinkToGeoTiff(dst_dir, lambda i, da: f"out_{i}.tif"), ex) snippet source | anchor <!-- endSnippet -->

Note, that this example uses eotransform's streamed_process function to hide the I/O operations, using the compute resources more effectively.

Support & Documentation

Dependencies:

eotransform-xarray requires Python 3.8 and has these dependencies:

cfg eotransform>=1.8 xarray rioxarray numpy affine more_itertools snippet source | anchor <!-- endSnippet -->

Citation

If you find this repository useful, please consider giving it a star or a citation: bibtex @software{eotransform_xarray_2023_8002854, author = {Raml, Bernhard}, title = {eotransform-xarray}, month = jun, year = 2023, publisher = {Zenodo}, version = {2.4.1}, doi = {10.5281/zenodo.8002854}, url = {https://doi.org/10.5281/zenodo.8002854} }

Owner

  • Name: TU Wien - Department of Geodesy and Geoinformation
  • Login: TUW-GEO
  • Kind: organization
  • Location: Vienna, Austria

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: eotransform-xarray
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Bernhard
    family-names: Raml
    email: bernhard.raml@geo.tuwien.ac.at
    affiliation: TU Wien
    orcid: 'https://orcid.org/0000-0002-5357-0344'
repository-code: 'https://github.com/TUW-GEO/eotransform-xarray'
url: 'https://eotransform-xarray.readthedocs.io/'
abstract: >-
  The eotransform-xarray package provides common
  transformations on raster data represented as xarray) data
  structures, following the Transformer protocol of
  eotransform.
keywords:
  - data pipeline
  - streaming
  - raster data
  - earth observation
license: MIT
commit: 1e045bf
version: 2.4.1
date-released: '2023-06-04'

GitHub Events

Total
Last Year

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 170
  • Total Committers: 2
  • Avg Commits per committer: 85.0
  • Development Distribution Score (DDS): 0.165
Past Year
  • Commits: 87
  • Committers: 2
  • Avg Commits per committer: 43.5
  • Development Distribution Score (DDS): 0.253
Top Committers
Name Email Commits
Bernhard Raml b****l@g****t 142
GitHub Action a****n@g****m 28
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 0
  • Total pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: about 1 hour
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
  • SwamyDev (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 258 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 22
  • Total maintainers: 1
pypi.org: eotransform-xarray

Implements transformations on xarray data structures, to be used with eotransform streamed_process.

  • Versions: 22
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 258 Last month
Rankings
Dependent packages count: 6.6%
Downloads: 6.8%
Average: 22.7%
Forks count: 30.5%
Dependent repos count: 30.6%
Stargazers count: 39.1%
Maintainers (1)
Last synced: 8 months ago

Dependencies

.github/workflows/publish.yml actions
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.github/workflows/test_coverage.yml actions
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.github/workflows/test_platforms.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite